The invention relates to an electrocardiograph device that determines a patient's probability of death from cardiovascular disease.
In the United States, approximately 4.5 million patients per year enter emergency rooms (ERs) with symptoms suggesting accute cardiac disease, and of those, one third are subsequently admitted to Coronary Care Units (CCUs). A physician must decide whether triage options other than the CCU (e.g., intermediate care units, ward beds, observation units, or home care under close supervision) may be more appropriate. In addition to the patient's condition, to the extent it can be accurately assesed, other factors to be considered include the scarcity of facilities, continually increasing costs, and the new stricter cost containment strategies (e.g. diagnostic related groups (DRGs)). Such decisions are difficult because they require an accurate, reliable determination of a patient's true level of risk, and such determinations are themselves difficult to perform.
Hospitals currently release mortality data (i.e. the fraction of patients who die per year) that are not adjusted in accordance with differences in their respective patient populations. If such data are to be used as metrics of quality of medical care, these data should be calibrated in order to facilitate fair comparisons between hospitals with different patient populations.
In Pozen, et al. New Enqland J. of Med. 310, 1273-1278, 1984, a hand-held calculator was programmed to provide the emergency room physician with a patient's calculated likelihood of having acute ischemia. Its use depends on the physician's interpretation of the patient's ECG. It uses a logistic regression function with coeficients derived by stepwise regression analysis.
Electrocardiographs exist that imitate physician judgment by using feature recognition algorithms in conjunction with a rule based computer program to provide a qualitative diagnosis of a patient's condition.
Other electrocardiographs exist that use feature recognition data and feature measurements as inputs to a logistic regression formula to provide a quantitative measure of the possibility of ischemia (a type of heart attack).
The probability of ischemia is not the same as the probability of death, because there are other causes of acute and dangerous cardiac conditions. For example, a patient with new or unstable angina pectoris has approximately a 5 percent chance of dying, whereas a patient with a Killip Class IV myocardial infarction has an approximately 80 per cent chance of death. This is important because it is the probability of death, not the probability of ischemia, that is critical to a physician's triage decision.